1 Introduction

The Notebook is aimed to visualize the SNP frequency (Col vs Ler) in asy1 shattered hybrids. The SNP% is for Ler. The SNP% would be different specifically around centromeres coming from different non-disjunctions.

  • If shattered chromosome from non-disjunction in Meiosis I: with shattered arm: 33%; no shattered arm: 0% or 50%
  • if shattered chromosome from non-disjunction in Meiosis II: with shattered arm: 66% or 0%; no shattered arm: 0% or 50%

2 Outline

  1. load libraries and data

3 Input libraries and data

3.1 add libraries

library("tidyverse")
library("ggplot2")
library("ggpubr")

3.2 add data

3.2.1 10kb

asy1.SNP.10kb <- read.csv("/Users/wendy/Desktop/Lab/arabidopsis/binbygeno_asy1_10kb_20220310.txt",sep = "\t")
head(asy1.SNP.10kb)

3.2.2 100kb

```r
asy1.SNP.100kb <- read.csv(\/Users/wendy/Desktop/Lab/arabidopsis/binbygeno_asy1_100kb_20220310.txt\,sep = \\t\)
head(asy1.SNP.100kb)

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# take data in Chr1 #
## 10kb ##

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```r
pos.chr1.10kb <- asy1.SNP.10kb$Start[asy1.SNP.10kb$Chrom == 'Chr1']
ler.chr1.10kb <- asy1.SNP.10kb$v.Gaetan.aa.C.102.Obs.B[asy1.SNP.10kb$Chrom == 'Chr1']
chr1.10kb <- data.frame(pos.chr1.10kb,ler.chr1.10kb)
snp.chr1.10kb <- list(pos.chr1.10kb)

4 Chr1

4.1 100kb

```r
pos.chr1.100kb <- asy1.SNP.100kb$Start[asy1.SNP.100kb$Chrom == 'Chr1']
ler.chr1.100kb <- asy1.SNP.100kb$v.Gaetan.aa.C.102.Obs.B[asy1.SNP.100kb$Chrom == 'Chr1']
chr1.100kb <- data.frame(pos.chr1.100kb, ler.chr1.100kb)

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# SNP frequency plots #
## 10kb ##

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```r
snp.10kb <- ggplot(chr1.10kb, aes(pos.chr1.10kb,ler.chr1.10kb)) +
  geom_point(alpha=.5) +
  scale_color_manual(values = c("#E69F00")) +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") + 
  scale_x_continuous(name="Chromosome 1", breaks = NULL) +
  scale_y_continuous(name="Ler-1 allel Frequency")
snp.10kb

5 save

5.1 10kb

ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_snp_chr1_10kb_20220629.png",width = 6, height = 2)

6 dosage data

6.1 5kb only chr1

asy1.dos.10k <- read.csv("/Users/wendy/Desktop/Lab/arabidopsis/binbysam-Gaetan-102-2ctrl-10kb-20210916.txt",sep = "\t")
asy1.strt <- asy1.dos.10k$Strt[asy1.dos.10k$Chrom == 'Chr1']
asy1.Cov <- asy1.dos.10k$Gaetan_aa_C_102.LC_C_1_21_ctrl[asy1.dos.10k$Chrom == 'Chr1']
asy1.dos.Chr1 <- data.frame(asy1.strt, asy1.Cov)
head(asy1.dos.Chr1)

6.2 compare dos and snp locations

dos.chr1.strt.new <- c()
dos.chr1.cov.new <- c()
for (a in asy1.dos.Chr1$asy1.strt) {
  pos <- a-1
  for (b in snp.chr1.10kb[[1]]) {
    if (pos == b) {
      dos.chr1.strt.new <- c(dos.chr1.strt.new, pos)
      dos.chr1.cov.new <- c(dos.chr1.cov.new, asy1.dos.Chr1$asy1.Cov[asy1.strt == a])
    }
  }
}
length(dos.chr1.strt.new)
[1] 2771
length(dos.chr1.cov.new)
[1] 2771
length(snp.chr1.10kb[[1]])
[1] 2771

6.3 combine snp and dos with same positions

dos.chr1.cov.new <- as.numeric(dos.chr1.cov.new)
snp.dos.chr1.10k <- data.frame(dos.chr1.strt.new, dos.chr1.cov.new, ler.chr1.10kb)
head(snp.dos.chr1.10k)

7 plot snp

snp.10kb <- ggplot(snp.dos.chr1.10k, aes(dos.chr1.strt.new,ler.chr1.10kb)) +
  geom_point(alpha=.5) +
  scale_color_manual(values = c("#E69F00")) +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") + 
  scale_x_continuous(name="Chromosome 1", breaks = NULL) +
  scale_y_continuous(name="Ler-1 allel Frequency")
snp.10kb

ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_snp_chr1_10kb_20220629.png",width = 6, height = 1.5)

8 plot dosage

dos.10kb <- ggplot(snp.dos.chr1.10k, aes(dos.chr1.strt.new,dos.chr1.cov.new)) +
  geom_point(alpha=.5,color = "navy") +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") +
  scale_x_continuous(name = "", breaks = NULL) +
  scale_y_continuous(name = "Relative read coverage",limits = c(1,4))
dos.10kb
Warning: Removed 18 rows containing missing values (geom_point).

ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_dos_chr1_10kb_20220629.png",width = 6, height = 1.5)
Warning: Removed 18 rows containing missing values (geom_point).
snp.dos.chr1.10k.1217 <- snp.dos.chr1.10k %>%
  filter(12000000 <= dos.chr1.strt.new & dos.chr1.strt.new <= 17000000)
snp.dos.chr1.10k.1217

9 save file

```r
write.table(snp.dos.chr1.10k, file = \/Users/wendy/Desktop/Lab/arabidopsis/snp_dos_chr1_10kb_20220315.txt\, sep = \\t\, row.names = TRUE, col.names = TRUE)

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# plot snp #

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```r
snp.10kb <- ggplot(snp.dos.chr1.10k.1217, aes(dos.chr1.strt.new,ler.chr1.10kb)) +
  geom_point(alpha=.5) +
  scale_color_manual(values = c("#E69F00")) +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") + 
  scale_x_continuous(name="Chromosome 1: 10Mb to 16Mb", breaks = NULL) +
  scale_y_continuous(name="Ler-1 allel Frequency")
snp.10kb

ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_snp_chr1_1217_20220629.png",width = 6, height = 1.5)

10 plot dosage

dos.10kb <- ggplot(snp.dos.chr1.10k.1217, aes(dos.chr1.strt.new,dos.chr1.cov.new)) +
  geom_point(alpha=.5,color = "navy") +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") +
  scale_x_continuous(name = "", breaks = NULL) +
  scale_y_continuous(name = "Relative read coverage",limits = c(1,4))
dos.10kb
Warning: Removed 7 rows containing missing values (geom_point).

ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_dos_chr1_1217_20220629.png",width = 6, height = 1.5)
Warning: Removed 7 rows containing missing values (geom_point).

11 plot dos and snp together

dos.snp.10k <- ggplot(snp.dos.chr1.10k, aes(x = dos.chr1.strt.new)) +
  geom_point(aes(y=dos.chr1.cov.new),alpha=.6,color="orange") +
  geom_point(aes(y=ler.chr1.10kb/25),alpha=.5,color="navy") +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 14, margin = margin(t=10)), axis.title.y = element_text(size = 14, margin = margin(r=10))) +
  scale_x_continuous(name = "Chromosome 1", breaks = NULL) +
  scale_y_continuous(name = "Relative Read Coverage",sec.axis = sec_axis(trans = ~.*25, name = "Ler SNP Frequency"))
dos.snp.10k

12 save plot

ggsave("/Users/wendy/Desktop/manuscript-ASY1/snp_dos_chr1_10kb_20220622.png", height = 4, width = 8)

13 dosage plot

dos.10kb <- ggplot(asy1.dos.Chr1, aes(asy1.strt,as.numeric(asy1.Cov))) +
  geom_point(alpha=.5) +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") +
  scale_x_continuous(name = "", breaks = NULL) +
  scale_y_continuous(name = "Relative read coverage",limits = c(1,4))
dos.10kb
Warning in FUN(X[[i]], ...) : NAs introduced by coercion
Warning: Removed 31 rows containing missing values (geom_point).

ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/dosage-chr1-20220629.png", width = 6, height = 1.5)
Warning in FUN(X[[i]], ...) : NAs introduced by coercion
Warning: Removed 31 rows containing missing values (geom_point).

14 arrange two plots into one

onepage <- ggarrange(dos.10kb, snp.10kb, ncol = 1, nrow = 2)
Warning in FUN(X[[i]], ...) : NAs introduced by coercion
Warning: Removed 31 rows containing missing values (geom_point).
onepage

15 save onepage

ggsave("/Users/wendy/Desktop/manuscript-ASY1/asy1_snp_10kb_20220622.png", width = 6, height = 3)
---
title: "Arabidopsis_SNP_freq_visualization"
output:
  html_notebook:
    number_sections: yes
    toc: yes
    toc_float: yes
  html_document:
    df_print: paged
    toc: yes
---

# Introduction #
The Notebook is aimed to visualize the SNP frequency (Col vs Ler) in asy1 shattered hybrids.
The SNP% is for Ler. The SNP% would be different specifically around centromeres coming from different non-disjunctions.

- If shattered chromosome from non-disjunction in Meiosis I:
  with shattered arm: 33%; no shattered arm: 0% or 50%
- if shattered chromosome from non-disjunction in Meiosis II:
  with shattered arm: 66% or 0%; no shattered arm: 0% or 50%

# Outline #
1. load libraries and data
2. 

# Input libraries and data #
## add libraries ##
```{r}
library("tidyverse")
library("ggplot2")
library("ggpubr")
```


## add data ##
### 10kb ###
```{r}
asy1.SNP.10kb <- read.csv("/Users/wendy/Desktop/Lab/arabidopsis/binbygeno_asy1_10kb_20220310.txt",sep = "\t")
head(asy1.SNP.10kb)
```


### 100kb ###
```{r}
asy1.SNP.100kb <- read.csv("/Users/wendy/Desktop/Lab/arabidopsis/binbygeno_asy1_100kb_20220310.txt",sep = "\t")
head(asy1.SNP.100kb)
```

# take data in Chr1 #
## 10kb ##
```{r}
pos.chr1.10kb <- asy1.SNP.10kb$Start[asy1.SNP.10kb$Chrom == 'Chr1']
ler.chr1.10kb <- asy1.SNP.10kb$v.Gaetan.aa.C.102.Obs.B[asy1.SNP.10kb$Chrom == 'Chr1']
chr1.10kb <- data.frame(pos.chr1.10kb,ler.chr1.10kb)
snp.chr1.10kb <- list(pos.chr1.10kb)
```

# Chr1 #
## 100kb ##
```{r}
pos.chr1.100kb <- asy1.SNP.100kb$Start[asy1.SNP.100kb$Chrom == 'Chr1']
ler.chr1.100kb <- asy1.SNP.100kb$v.Gaetan.aa.C.102.Obs.B[asy1.SNP.100kb$Chrom == 'Chr1']
chr1.100kb <- data.frame(pos.chr1.100kb, ler.chr1.100kb)
```


# SNP frequency plots #
## 10kb ##
```{r}
snp.10kb <- ggplot(chr1.10kb, aes(pos.chr1.10kb,ler.chr1.10kb)) +
  geom_point(alpha=.5) +
  scale_color_manual(values = c("#E69F00")) +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") + 
  scale_x_continuous(name="Chromosome 1", breaks = NULL) +
  scale_y_continuous(name="Ler-1 allel Frequency")
snp.10kb
```


# save #
## 10kb ##
```{r}
ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_snp_chr1_10kb_20220629.png",width = 6, height = 2)
```

# dosage data #
## 5kb only chr1 ##
```{r}
asy1.dos.10k <- read.csv("/Users/wendy/Desktop/Lab/arabidopsis/binbysam-Gaetan-102-2ctrl-10kb-20210916.txt",sep = "\t")
asy1.strt <- asy1.dos.10k$Strt[asy1.dos.10k$Chrom == 'Chr1']
asy1.Cov <- asy1.dos.10k$Gaetan_aa_C_102.LC_C_1_21_ctrl[asy1.dos.10k$Chrom == 'Chr1']
asy1.dos.Chr1 <- data.frame(asy1.strt, asy1.Cov)
head(asy1.dos.Chr1)
```
## compare dos and snp locations ##
```{r}
dos.chr1.strt.new <- c()
dos.chr1.cov.new <- c()
for (a in asy1.dos.Chr1$asy1.strt) {
  pos <- a-1
  for (b in snp.chr1.10kb[[1]]) {
    if (pos == b) {
      dos.chr1.strt.new <- c(dos.chr1.strt.new, pos)
      dos.chr1.cov.new <- c(dos.chr1.cov.new, asy1.dos.Chr1$asy1.Cov[asy1.strt == a])
    }
  }
}
length(dos.chr1.strt.new)
length(dos.chr1.cov.new)
length(snp.chr1.10kb[[1]])
```

## combine snp and dos with same positions ##
```{r}
dos.chr1.cov.new <- as.numeric(dos.chr1.cov.new)
snp.dos.chr1.10k <- data.frame(dos.chr1.strt.new, dos.chr1.cov.new, ler.chr1.10kb)
head(snp.dos.chr1.10k)
```

# plot snp #
```{r}
snp.10kb <- ggplot(snp.dos.chr1.10k, aes(dos.chr1.strt.new,ler.chr1.10kb)) +
  geom_point(alpha=.5) +
  scale_color_manual(values = c("#E69F00")) +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") + 
  scale_x_continuous(name="Chromosome 1", breaks = NULL) +
  scale_y_continuous(name="Ler-1 allel Frequency")
snp.10kb
```

```{r}
ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_snp_chr1_10kb_20220629.png",width = 6, height = 1.5)
```


# plot dosage #
```{r}
dos.10kb <- ggplot(snp.dos.chr1.10k, aes(dos.chr1.strt.new,dos.chr1.cov.new)) +
  geom_point(alpha=.5,color = "navy") +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") +
  scale_x_continuous(name = "", breaks = NULL) +
  scale_y_continuous(name = "Relative read coverage",limits = c(1,4))
dos.10kb
```

```{r}
ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_dos_chr1_10kb_20220629.png",width = 6, height = 1.5)
```


```{r}
snp.dos.chr1.10k.1217 <- snp.dos.chr1.10k %>%
  filter(12000000 <= dos.chr1.strt.new & dos.chr1.strt.new <= 17000000)
snp.dos.chr1.10k.1217
```

# save file #
```{r}
write.table(snp.dos.chr1.10k, file = "/Users/wendy/Desktop/Lab/arabidopsis/snp_dos_chr1_10kb_20220315.txt", sep = "\t", row.names = TRUE, col.names = TRUE)
```

# plot snp #
```{r}
snp.10kb <- ggplot(snp.dos.chr1.10k.1217, aes(dos.chr1.strt.new,ler.chr1.10kb)) +
  geom_point(alpha=.5) +
  scale_color_manual(values = c("#E69F00")) +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") + 
  scale_x_continuous(name="Chromosome 1: 10Mb to 16Mb", breaks = NULL) +
  scale_y_continuous(name="Ler-1 allel Frequency")
snp.10kb
```

```{r}
ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_snp_chr1_1217_20220629.png",width = 6, height = 1.5)
```

# plot dosage #
```{r}
dos.10kb <- ggplot(snp.dos.chr1.10k.1217, aes(dos.chr1.strt.new,dos.chr1.cov.new)) +
  geom_point(alpha=.5,color = "navy") +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") +
  scale_x_continuous(name = "", breaks = NULL) +
  scale_y_continuous(name = "Relative read coverage",limits = c(1,4))
dos.10kb
```

```{r}
ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/asy1_dos_chr1_1217_20220629.png",width = 6, height = 1.5)
```


# plot dos and snp together #
```{r}
dos.snp.10k <- ggplot(snp.dos.chr1.10k.1217, aes(x = dos.chr1.strt.new)) +
  geom_point(aes(y=dos.chr1.cov.new),alpha=.6,color="orange") +
  geom_point(aes(y=ler.chr1.10kb/25),alpha=.5,color="navy") +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 14, margin = margin(t=10)), axis.title.y = element_text(size = 14, margin = margin(r=10))) +
  scale_x_continuous(name = "Chromosome 1", breaks = NULL) +
  scale_y_continuous(name = "Relative Read Coverage",sec.axis = sec_axis(trans = ~.*25, name = "Ler SNP Frequency"))
dos.snp.10k
```

# save plot #
```{r}
ggsave("/Users/wendy/Desktop/manuscript-ASY1/snp_dos_chr1_10kb_20220622.png", height = 4, width = 8)
```


# dosage plot #
```{r}
dos.10kb <- ggplot(asy1.dos.Chr1, aes(asy1.strt,as.numeric(asy1.Cov))) +
  geom_point(alpha=.5) +
  theme(axis.text.x = element_text(size = 8, angle = 90), axis.title.x = element_text(size = 10, margin = margin(t=10)), axis.title.y = element_text(size = 8, margin = margin(r=10)), legend.position = "None") +
  scale_x_continuous(name = "", breaks = NULL) +
  scale_y_continuous(name = "Relative read coverage",limits = c(1,4))
dos.10kb
```

```{r}
ggsave("/Users/wendy/Desktop/Lab/arabidopsis/plots/dosage-chr1-20220629.png", width = 6, height = 1.5)
```

# arrange two plots into one #
```{r}
onepage <- ggarrange(dos.10kb, snp.10kb, ncol = 1, nrow = 2)
onepage
```

# save onepage #
```{r}
ggsave("/Users/wendy/Desktop/manuscript-ASY1/asy1_snp_10kb_20220622.png", width = 6, height = 3)
```




